People often use science fiction to illustrate philosophy all the time. From ethical quandaries to the very nature of existence, science fiction's most famous texts are tailor-made for exploring philosophical ideas.

// Natural Language Processing, or NLP, is a field of computer science, artificial intelligence, and linguistics concerned with the interactions between computers and human (natural) languages. Here...

In a narrow sense, “digital humanities” refers to the application of quantitative, computer-based methods for humanities research, usually complementing traditional qualitative methods (note that this definition involves both readings of “digital”). The important point is that it is humanities research, i.e., you’re applying these methods to answer a humanities research question.

In a wider sense, it may also refer to the application of computer-based tools in humanities research (note that this definition does not require the use of quantitative methods). For example, creating a digital edition is not digital humanities in the narrow sense (because it does not use quantitative methods), but it is in the wider sense. I think this extension is useful, because the creation of digital resources is a prerequisite for digital humanities in the narrow sense.

The SemantAPI toolkit is a free, open source toolkit intended for a quick and easy comparison of the most popular NLP and sentiment analysis solutions on the market. The toolkit offers 2 independent analysis applications: SemantAPI.Robot and SemantAPI.Human, as well as a data stream application, GNIP to CSV.

Datumbox offers a large number of off-the-shelf Classifiers and Natural Language Processing services which can be used in a broad spectrum of applications including: Sentiment Analysis, Topic Classification, Language Detection, Subjectivity Analysis, Spam Detection, Reading Assessment, Keyword and Text Extraction and more. All services are accessible via our powerful REST API which allows you to develop your own smart Applications in no time.

Some of the biggest challenges for the scientific community today involve understanding the principles and mechanisms that underlie natural language use on the Web. An example of long-standing problem is language ambiguity; when somebody types the word “Rio” in a query do they mean the city, a movie, a casino, or something else? Understanding the difference can be crucial to help users get the answer they are looking for. In the past few years, a significant effort in industry and academia has focused on disambiguating language with respect to Web-scale knowledge repositories such as Wikipedia and Freebase.

The use of language has an extended effect upon society and culture. This effect cannot be determined exactly and the intent behind its use is not the production of change but communication between individuals across time and space. Society uses language and the language grows with time and the number of it’s users.

Language and philosophy by Chomsky

It's dogma that language and communication are the same thing. Any action you carry out communicates something. "A gesture, a hairstyle, almost anything. Sure, language behaviour also communicates something."

"Beyond that, almost all language is not involved in communication. We all know that, you can't go one minute without talking to yourself, it would take a tremendous effort of will to not think about what's going on in your head. That's communication with self."

Constraints of Knowledge

Just like a dog is incapable of learning quantum physics, humans have their own limits of intelligence and understanding. "This really shouldn't surprise anyone, we know we have constraints on what we can do physically, we can't fly like eagles let say. If there are also limits to our cognitive capacities, that really shouldn't surprise anyone. It would just say we're biological organisms, not angels."

"Furthermore, instead of being unhappy about our limits we should be happy about them. If there were no constraints you couldn't learn anything, you couldn't acquire anything, you couldn't discover anything. If you don't have limits, you don't have scope, there's a logical connection between limit and scope. The fact that there are limits on what you can be, enables you to become what you did become. Instead of living a pointless existence."

Limits of Science.

The point of Science is to understand as much as we can about the nature of things, a worthy objective. It is not however meant to understand everything, that's impossible.

"Science can deal with simple things, but it doesn't get anywhere when it gets to complex things. It's hard, it's hard to explain even simple things, but when it does we find all kinds of surprising things, for example, you find our only intelligible concept of the world is wrong."

Future syntax

As described by Terence McKenna in Ordinary Language, Visible Language and Virtual Reality:

The starships of the future that will explore the high frontier of the unknown will be syntactical. The engineers of the future will be poets.

This is what virtual reality holds out to us—the possibility of walking in to the constructs of the imagination. In a way culture is that. I mean our cities, bridges, highways, airliners and art galleries are condensations out of the imagination, but at tremendous cost because we must make them out of matter. Once we can make them out of light, out of electrons, then we won't build skyscrapers a hundred and twenty stories high, we'll build them as high as we want.

Roof height will no longer be a factor ruled by cost effectiveness and gravity, it will be a parameter ruled by the imagination as well all other parameters and then we will discover what man truly is—when we are able to erect, stabilize, share and explore our dreams in a kind of virtual hyperspace that, carefully analyzed, is seen to be linguistic.

An analysis of mood patterns distilled from half a billion tweets has produced a civilization-scale picture of how moods rise and fall in tandem, over time and across the world.

The details seem intuitive: positive feelings peaking in the morning, dipping during work and rising at day’s end; negativity accumulated over the workweek dissipating late on Friday afternoon. But they’ve proved surprisingly tricky to measure.

NLP Logix uses next-generation sentiment analysis to increase customer loyalty and retention. Sentiment Analysis refers to the use of natural language processing, text analysis and computational linguistics to identify and extract subjective information in source materials. This cutting-edge technology gives an organization the ability to monitor client or customer sentiment on a real-time basis, and when combined with other transactional data, can provide a probability score of overall client satisfaction.

This document defines the Ontology for Media Resources 1.0. The term "Ontology" is used in its broadest possible definition: a core vocabulary. The intent of this vocabulary is to bridge the different descriptions of media resources, and provide a core set of descriptive properties. This document defines a core set of metadata properties for media resources, along with their mappings to elements from a set of existing metadata formats. Besides that, the document presents a Semantic Web compatible implementation of the abstract ontology using RDF/OWL.

Watson, the IBM computer that will compete on Jeopardy!, represents an impressive leap forward in analytics and systems design.

Mariana Soffer's insight:

For the first time, IBM will open up Watson as a development platform in the Cloud to spur innovation and fuel a new ecosystem of entrepreneurial software app providers who will bring forward a new generation of applications infused with Watson's cognitive computing intelligence.

This website provides a live demo for predicting the sentiment of movie reviews. Most sentiment prediction systems work just by looking at words in isolation, giving positive points for positive words and negative points for negative words and then summing up these points. That way, the order of words is ignored and important information is lost. In constrast, our new deep learning model actually builds up a representation of whole sentences based on the sentence structure. It computes the sentiment based on how words compose the meaning of longer phrases. This way, the model is not as easily fooled as previous models. For example, our model learned that funny and witty are positive but the following sentence is still negative overall:

This movie was actually neither that funny, nor super witty.

The underlying technology of this demo is based on a new type of Recursive Neural Network that builds on top of grammatical structures. You can also browse the Stanford Sentiment Treebank, the dataset on which this model was trained. The model and dataset are described in an upcoming EMNLP paper. Of course, no model is perfect. You can help the model learn even more by labeling sentences we think would help the model or those you try in the live demo.

The bigger your company gets, however, the harder it becomes to keep a handle on how everyone feels about your brand. For large companies with thousands of daily mentions on social media, news sites and blogs, it’s extremely difficult to do manually.

Obviously language is easier than visual recognition and linguists and programmers have spent 50 years trying to program semantics as software. While IBM's Jeopardy-winning Watson system and Google Translate are high profile, successful applications of language technologies, the humorous answers and mistranslations they sometimes produce are evidence of the continuing difficulty of the problem: that computers lack a lifetime of experience. Using the context in which a word is used, an intrinsic understanding of syntax and logic, and a sense of the speaker's intention, we can intuit what another person is telling us and programs cannot.

First, we need to examine “meaning” itself, and expose a mistake, a very basic mistake, in how many people think about it. To say that some event means something without at least some implicit understanding of who it means something to is to express an incomplete idea, no different than sentence fragments declaring that “Went to the bank” or “Exploded.” Without first specifying a particular subject and/or object, the very idea of meaning is incoherent.

The fashionable ideology that “artificial” lacks the inherent goodness of “natural” is an appealing, but hopelessly simplistic notion of the intellectually chic. Artifice is the result of a deliberate intent to make. Nature also “makes” things, using a set of basic building blocks common throughout the universe. Exchanging infinite time for deliberate design, nature has ingeniously built plants, planets, galaxies and unimaginable constructs which seem to structure the univers itself.

"Literacy is changing. It really is. Even in my grade one classroom as the students begin to learn their letters and sounds, as they start to put those letters and sounds together into words, and as they take their first hesitant steps to read and write —literacy is changing.

The change in our classroom was subtle at first. When my students began writing the word we with two i’s, I smiled and talked about the more traditional spelling of the word. When students came to school with a clear understanding of what it meant to get to the next level or to have several lives, I took notice of the new vocabulary they had."

Putting young students together with technology creates a win-win situation in this classroom. Learn how one teacher has her students writing in blogs to share their work, using twitter, learning vocabulary (such as pingback) and much more. This post is complete with a video where students provide definitions of words and share how they use technology in their classroom.

Insight: …information as dots on a screen and the story is the way to connect those dots… "Professor Brian Sturm presents storytelling as a way of organizing information, conveying emotions, and building community.

Mariana Soffer's insight:

Professor Brian Sturm presents storytelling as a way of organizing information, conveying emotions, and building community. A model of #storytelling as altered state of consciousness (the story trance) is presented that includes 16 portals to altered states. Three stories are told to illustrate the theoretical model: Truth and Story; What happens when you really listen; and The stone cutter. Storytelling ethics and the need for trust and truth are discussed

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